The program md.f implements a simple molecular dynamics simulation in continuous real space. The velocity Verlet algorIthm is used to implement the time stepping. The force and energy computations are performed in parallel, as is the time integration. (The program uses some Fortran90 features, so an F90 compiler may be needed.)
標(biāo)簽： implements continuous simulation The
上傳時(shí)間： 2016-04-03
上傳用戶：zhaiye
When working with mathematical simulations or engineering problems, it is not unusual to handle curves that contains thousands of points. Usually, displaying all the points is not useful, a number of them will be rendered on the same pixel since the screen precision is finite. Hence, you use a lot of resource for nothing! This article presents a fast 2D-line approximation algorIthm based on the Douglas-Peucker algorIthm (see [1]), well-known in the cartography community. It computes a hull, scaled by a tolerance factor, around the curve by choosing a minimum of key points. This algorIthm has several advantages: 這是一個(gè)基于Douglas-Peucker算法的二維估值算法。
標(biāo)簽： mathematical engineering simulations problems
上傳時(shí)間： 2013-12-20
上傳用戶：changeboy
On-Line MCMC Bayesian Model Selection This demo demonstrates how to use the sequential Monte Carlo algorIthm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
標(biāo)簽： demonstrates sequential Selection Bayesian
上傳時(shí)間： 2016-04-07
上傳用戶：lindor
The program implements three large-margin thresholded ensemble algorIthms for ordinal regression. It includes an improved RankBoost algorIthm, the ORBoost-LR algorIthm, and the ORBoost-All algorIthm.
標(biāo)簽： large-margin thresholded implements algorIthms
上傳時(shí)間： 2014-10-28
上傳用戶：zhichenglu
The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorIthm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient state-of-the-art resampling routines. These are generic and suitable for any application. For details, please refer to Rao-Blackwellised Particle Filtering for Fault Diagnosis and On Sequential Simulation-Based Methods for Bayesian Filtering After downloading the file, type "tar -xf demo_rbpf_gauss.tar" to uncompress it. This creates the directory webalgorIthm containing the required m files. Go to this directory, load matlab and run the demo.
標(biāo)簽： filtering particle Blackwellised conditionall
上傳時(shí)間： 2014-12-05
上傳用戶：410805624
LEGClust算法更新，上次上傳的代碼發(fā)現(xiàn)有些問(wèn)題，現(xiàn)已更正，A Clustering algorIthm Based on Layered Entropic Subgraphs
上傳時(shí)間： 2013-12-20
上傳用戶：yiwen213
KMEANS Trains a k means cluster model.CENTRES = KMEANS(CENTRES, DATA, OPTIONS) uses the batch K-means algorIthm to set the centres of a cluster model. The matrix DATA represents the data which is being clustered, with each row corresponding to a vector. The sum of squares error function is used. The point at which a local minimum is achieved is returned as CENTRES.
標(biāo)簽： CENTRES KMEANS OPTIONS cluster
上傳時(shí)間： 2014-01-07
上傳用戶：zhouli
Probability distribution functions. estimation - (dir) Probability distribution estimation. dsamp - Generates samples from discrete distribution. erfc2 - Normal cumulative distribution function. gmmsamp - Generates sample from Gaussian mixture model. gsamp - Generates sample from Gaussian distribution. cmeans - C-means (or K-means) clustering algorIthm. mahalan - Computes Mahalanobis distance. pdfgauss - Computes probability for Gaussian distribution. pdfgmm - Computes probability for Gaussian mixture model. sigmoid - Evaluates sigmoid function.
標(biāo)簽： distribution Probability estimation functions
上傳時(shí)間： 2016-04-28
上傳用戶：13188549192
堆排序算法，the heap sort algorIthm
標(biāo)簽： 排序算法
上傳時(shí)間： 2016-05-04
上傳用戶：磊子226
支持向量機(jī)，用于分類。Classify using (a very simple implementation of) the support vector machine algorIthm
標(biāo)簽： 支持向量機(jī)
上傳時(shí)間： 2014-01-11
上傳用戶：hphh
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